Machine Learning Engineer, Growth Platform

Sourced from jobera.com

Stripe is seeking a Machine Learning Engineer for its Growth Platform team in San Francisco to build and operate production ML systems that drive product recommendations and user engagement. The role involves designing recommendation models, contextual bandits, and agent-based capabilities while owning the full lifecycle from feature development to deployment and monitoring. Candidates will collaborate with data scientists and product partners to translate business problems into scalable technical solutions.

• Design, train, evaluate, deploy, and maintain models for recommendation, ranking, and personalized action selection.
• Improve contextual bandit and policy-learning approaches for adaptive recommendations.
• Build agent-based recommendation capabilities using business context.
• Develop reliable data and feature pipelines for training and inference.
• Build reusable tooling for model evaluation, retraining, and safe rollout.
• Own quality and operation of ML components including monitoring and debugging.

• 3+ years of industry experience in machine learning engineering or software engineering.
• Strong programming skills in Python with experience writing tested production code.
• Practical experience with ML frameworks such as PyTorch, TensorFlow, XGBoost, or scikit-learn.
• Experience building data/feature pipelines and proficiency in SQL.
• Familiarity with distributed data processing tools like Spark or PySpark.
• Strong understanding of statistics, model evaluation, and experimentation.

• Experience with recommendation systems, ranking, personalization, or marketplace optimization.
• Experience with contextual bandits, policy learning, causal inference, or off-policy evaluation.
• Experience building and evaluating LLM applications (embeddings, structured extraction).
• Experience building reusable ML capabilities used by multiple products or teams.